This paper is concerned with the design of a state feedback control scheme for variable stiffness actuated (VSA) robots, which guarantees prescribed performance of the tracking errors despite the low range of mechanical stiffness. The controller does not assume knowledge of the actual system dynamics nor does it utilize approximating structures (e.g., neural networks and fuzzy systems) to acquire such knowledge, leading to a low complexity design. Simulation studies, incorporating a model validated on data from an actual variable stiffness actuator (VSA) at a multi-degrees-of-freedom robot, are performed. Comparison with a gain scheduling solution reveals the superiority of the proposed scheme with respect to performance and robustness.Index Terms-Flexible joint robot control, nonlinear control, prescribed performance control (PPC), robust robot control, uncertain systems, variable stiffness actuators (VSAs).
In this paper, the problem of deriving a continuous, state-feedback controller for a class of multiinput multioutput feedback linearizable systems is considered with special emphasis on controller simplification and reduction of the overall design complexity with respect to the current state of the art. The proposed scheme achieves prescribed bounds on the transient and steady-state performance of the output tracking errors despite the uncertainty in system nonlinearities. Contrary to the current state of the art, however, only a single neural network is utilized to approximate a scalar function that partly incorporates the system nonlinearities. Furthermore, the loss of model controllability problem, typically introduced owing to approximation model singularities, is avoided without attaching additional complexity to the control or adaptive law. Simulations are performed to verify and clarify the theoretical findings.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.